LanguageNet: Learning to Find Sense Relevant Example Sentences
Shang-Chien Cheng | Jhih-Jie Chen | Chingyu Yang | Jason Chang
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
In this paper, we present a system, LanguageNet, which can help second language learners to search for different meanings and usages of a word. We disambiguate word senses based on the pairs of an English word and its corresponding Chinese translations in a parallel corpus, UM-Corpus. The process involved performing word alignment, learning vector space representations of words and training a classifier to distinguish words into groups of senses. LanguageNet directly shows the definition of a sense, bilingual synonyms and sense relevant examples.